Deep brain stimulation (DBS) is a technology designed to treat some neural disorders and abnormal neuronal activity such as Parkinson's disease. However, it has not been clear how periodic electrical stimuli can reduce the symptoms. The objective of this study is to test the hypothesis that the periodic signals can enhance endogenous signals in the network through stochastic resonance in a physiologically realistic neuron model of the central nervous system. In the computer simulations, two kinds of periodic waveforms were applied as extracellular sub-threshold electric stimuli, while the peak-to-baseline ratio (PBR) calculated from the power spectra of transmembrane potentials at the soma was used to quantify the detection of weak signals. It was shown that the PBR was increased, maximized, and then decreased as the frequency the periodic pulsatile stimuli increased, implying a resonance phenomenon depending on the frequency. It was concluded that the periodic electric stimuli utilized for DBS could play a key role in improving detection of weak signals when the amplitude and frequency of electric stimuli are appropriately set. Moreover, these results suggests a novel phenomenon for frequency dependent stochastic resonance capable of enhancing signals at specific frequencies.